Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

The team

The Tooling team builds shared systems that make data reliable, discoverable, governable, efficient, and easy to use. Our work spans data quality, lineage, metadata, ownership, observability, lifecycle management, optimization, and self-service workflows for Data Engineering, Data Science, Experimentation, Machine Learning, and product teams.

The role

We are looking for a Senior Software Engineer to design, build, and operate high-leverage data tooling used across Roblox. You will own substantial technical work from problem discovery through production rollout, turning complex operational signals into clear, dependable workflows.

A key focus for this role is intelligent automation for data operations: helping people and systems discover relevant data, diagnose quality or pipeline issues, understand cost and lifecycle signals, and take safe next steps. You will build these capabilities with strong evaluation, observability, and human oversight.

You will

Design, implement, and operate shared services, frameworks, and developer experiences for data quality, lineage, metadata, ownership, observability, lifecycle management, and optimization.
Turn signals such as freshness, quality failures, lineage, usage, and compute or storage cost into actionable alerts, recommendations, dashboards, and workflows.
Build AI-assisted or agentic experiences that help users investigate data questions and operational issues, with appropriate permissions, traceability, safety checks, and human approval for consequential actions.
Develop evaluation infrastructure for automated recommendations and actions, including reproducible tests, measurable quality criteria, regression checks, and monitoring for failures or unintended behavior.
Improve how teams discover, validate, govern, and operate data products, reducing toil while preserving clear ownership and reliable controls.
Partner with Data Engineering, Data Science, Experimentation, ML, product, and infrastructure teams to understand needs and deliver reusable solutions rather than one-off fixes.
Own production readiness for your work: instrumentation, service health, rollout plans, incident response, and follow-through on reliability and usability improvements.
Lead technical design for projects or workstreams, communicate tradeoffs and risks clearly, and mentor engineers through reviews and collaborative problem-solving.

You have

Strong software engineering experience building and operating production systems, platforms, or developer tools.
Experience designing services or frameworks that are reused by multiple teams, with attention to reliability, maintainability, observability, and user experience.
Experience with data systems or operational workflows, for example, metadata, data quality, lineage, orchestration, monitoring, or large-scale pipeline operations.
Sound judgment for turning ambiguous problems into incremental, measurable solutions, and for balancing automation with appropriate safeguards.
Experience evaluating automated or AI-assisted systems using representative tests, measurable outcomes, and ongoing production feedback; familiarity with agentic workflows is especially relevant.
The ability to collaborate across engineering and data disciplines, influence technical decisions, and explain complex tradeoffs to varied audiences.